Copernicus Marine Environment Monitoring Service (CMEMS) evolution: new and innovative ocean data assimilation techniques

Project results are expected to contribute to: 1. Improved ocean monitoring and predictions, maintaining international leadership. 2. Enhanced utilisation by CMEMS users of advances in observations, reanalysis, analysis and forecasting systems. 3. Strengthened exchanges on data assimilation development between operational centres and the scientific community.

Projects must address all of the following research and innovation areas: 1. Coupled data assimilation across ocean components or forcings (e.g., ocean–biogeochemistry, ocean–sea-ice, ocean–waves–atmosphere); 2. Multi-scale methods assimilating high-resolution, high-frequency observations and constraining larger scales; 3. Methods for reliable estimation of analysis and forecast uncertainties; 4. Application of Artificial Intelligence in data assimilation (emulators, model error estimation, bias correction, scale separation, parameter estimation); 5. Utilisation of new observation types (Sentinel Expansion, next-generation missions, novel in-situ data) or higher-resolution existing streams; 6. Development of tools to systematically assess observing system impact on assimilation; 7. Creation of software infrastructure accommodating diverse assimilation techniques and facilitating algorithm sharing and HPC optimisation; 8. Development of validation and intercomparison protocols (data challenges, OSSEs) to quantify benefits of improved methods and new observations; 9. Demonstrations of downstream applications that leverage improved assimilation; 10. Active planning for transfer of research outputs to operational deployment in CMEMS.